# A prognostic risk prediction model for gastric cancer based on the EFNA4 and ETS1 regulatory axis in tumor cells

## TL;DR

This study identifies EFNA4 and ETS1 as key genes in gastric cancer and develops a risk prediction model to improve prognosis and treatment strategies.

## Contribution

The novel contribution is the development of an EFNA4-ETS1-based prognostic model for gastric cancer risk stratification.

## Key findings

- EFNA4 and ETS1 show distinct expression patterns in gastric cancer tissues.
- A risk signature based on EFNA4, ETS1, and tumor cell markers improves prognosis prediction.
- High EFNA4 expression correlates with good prognosis in gastric cancer, contrasting with its role in liver cancer.

## Abstract

Gastric cancer (GC) is a major cause of cancer-related deaths worldwide, and is characterised by intricate molecular mechanisms. However, analysis of its molecular and clinical characteristics is complicated by its histological and etiological heterogeneity. Dysregulation of the PI3K-Akt signalling pathway is common in GC. In this study, we have identified the hub gene Ephrin A4 (EFNA4) in the PI3K-Akt pathway based on transcriptome data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and ETS Proto-Oncogene 1 (ETS1) was a gene related to EFNA4. Using publicly accessible datasets, we conducted bioinformatics analyses to evaluate the expression profiles, functional roles, and prognostic significance of EFNA4 and ETS1 and further explored their relationship in GC. Subsequently, consensus clustering was performed on 373 TCGA-STAD datasets based on the expression matrices of EFNA4 and ETS1 to assess their interconnections with relevant signalling cascades and immune system components. To address the challenges posed by tumour heterogeneity and reveal the expression patterns of EFNA4 and ETS1 in GC tissues, we performed reanalysis of single-cell RNA sequencing (scRNA-seq) data of GC samples. We constructed a tumour-based risk signature for GC based on EFNA4, ETS1, and marker genes of the tumour cell cluster. The prognostic value of the prognosis prediction model was verified using TCGA database to facilitate the clinical application of tumour cell features in GC prognosis. Our study reveals EFNA4 and ETS1 expression patterns in GC, implicating their roles in pathogenesis. An integrated EFNA4-ETS1 prognostic model improves GC risk stratification. Although EFNA4 has been shown to promote metastasis in liver cancer, the contradictory mechanism of its high expression and good prognosis in GC remains to be elucidated, which may involve its antagonistic effects with ETS1, and requires further exploration.

The online version contains supplementary material available at 10.1038/s41598-025-21728-6.